1. Field of the Invention
The invention relates to an image processing system and, more particularly, to a parallel-pipelined image processing system that digitally processes pixels of successive image frames derived from a video camera to identify changes in a scene represented by the successive image frames.
2. Description of the Background Art
Many computer vision systems, for automatic surveillance and monitoring, seek to detect and segment transitory objects that appear temporarily in the system's field of view. Examples include traffic monitoring applications that count vehicles and automatic surveillance systems for security.
Various types of traffic monitoring systems that utilize vision processing systems are known in the prior art and examples thereof are respectively disclosed in U.S. Pat. Nos. 4,433,325, 4,847,772, 5,161,107 and 5,313,295.
Various image processing techniques that are useful in traffic monitoring systems have been discussed in the commonly assigned provisional patent application Ser. No. 60/006104 entitled "METHOD FOR CONSTRUCTING A REFERENCE IMAGE FROM AN IMAGE SEQUENCE" filed Oct. 31, 1995 and incorporated herein by reference. Also incorporated herein by reference is the disclosure of provisional patent application Ser. No. 06/006098 entitled "IMAGE-BASED OBJECT DETECTION AND TRACKING" filed Oct. 31, 1995 and the disclosure of provisional patent application Ser. No. 60/006100 (attorney docket DSRC 11912P) entitled "METHOD AND APPARATUS FOR DETERMINING AMBIENT CONDITIONS FROM AN IMAGE SEQUENCE" filed Oct. 31, 1995.
Further, the present invention makes use of pyramid teachings disclosed in U.S. Pat. No. 4,692,806, which issued to Anderson et al. on September 8, and image flow teachings disclosed in the article "Hierarchical Model-Based Motion Estimation" by Bergen et al., appearing in the Proceedings of the European Conference on Computer Vision, Springer-Verlag, 1992. Both of these teachings are incorporated herein by reference.
Although various image processing techniques are available, there is a need for a more robust image processing system for processing sequences of images to identify changes in the captured scene. A system that is computationally efficient and yet relatively inexpensive to implement would find use in applications such as traffic monitoring and security systems.